English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Two ways has been discussed to unlock the reasoning capability of a largelanguage model. The first one is prompt engineering and the second one is tocombine the multiple inferences of large language models, or the multi-agentdiscussion. Theoretically, this paper justifies the multi-agent discussionmechanisms from the symmetry of agents. Empirically, this paper reports theempirical results of the interplay of prompts and discussion mechanisms,revealing the empirical state-of-the-art performance of complex multi-agentmechanisms can be approached by carefully developed prompt engineering. Thispaper also proposes a scalable discussion mechanism based on conquer and merge,providing a simple multi-agent discussion solution with simple prompts butstate-of-the-art performance.

On the Discussion of Large Language Models: Symmetry of Agents and Interplay with Prompts